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ItemThe dopamine D1 receptor gene is associated with negative schizotypy in a non-clinical sampleGurvich, C ; Tan, EJ ; Bozaoglu, K ; Neill, E ; Louise, S ; Van Rheenen, TE ; Rossell, SL (ELSEVIER IRELAND LTD, 2016-01-30)
ItemDoes cognitive performance map to categorical diagnoses of schizophrenia, schizoaffective disorder and bipolar disorder? A discriminant functions analysisVan Rheenen, TE ; Bryce, S ; Tan, EJ ; Neill, E ; Gurvich, C ; Louise, S ; Rossell, SL (ELSEVIER, 2016-03-01)OBJECTIVES: Despite known overlaps in the pattern of cognitive impairments in individuals with bipolar disorder (BD), schizophrenia (SZ) and schizoaffective disorder (SZA), few studies have examined the extent to which cognitive performance validates traditional diagnostic boundaries in these groups. METHOD: Individuals with SZ (n=49), schizoaffective disorder (n=33) and BD (n=35) completed a battery of cognitive tests measuring the domains of processing speed, immediate memory, semantic memory, learning, working memory, executive function and sustained attention. RESULTS: A discriminant functions analysis revealed a significant function comprising semantic memory, immediate memory and processing speed that maximally separated patients with SZ from those with BD. Initial classification scores on the basis of this function showed modest diagnostic accuracy, owing in part to the misclassification of SZA patients as having SZ. When SZA patients were removed from the model, a second cross-validated classifier yielded slightly improved diagnostic accuracy and a single function solution, of which semantic memory loaded most heavily. CONCLUSIONS: A cluster of non-executive cognitive processes appears to have some validity in mapping onto traditional nosological boundaries. However, since semantic memory performance was the primary driver of the discrimination between BD and SZ, it is possible that performance differences between the disorders in this cognitive domain in particular, index separate underlying aetiologies.
ItemCharacterizing cognitive heterogeneity on the schizophrenia-bipolar disorder spectrumVan Rheenen, TE ; Lewandowski, KE ; Tan, EJ ; Ospina, LH ; Ongur, D ; Neill, E ; Gurvich, C ; Pantelis, C ; Malhotra, AK ; Rossell, SL ; Burdick, KE (CAMBRIDGE UNIV PRESS, 2017-07-01)BACKGROUND: Current group-average analysis suggests quantitative but not qualitative cognitive differences between schizophrenia (SZ) and bipolar disorder (BD). There is increasing recognition that cognitive within-group heterogeneity exists in both disorders, but it remains unclear as to whether between-group comparisons of performance in cognitive subgroups emerging from within each of these nosological categories uphold group-average findings. We addressed this by identifying cognitive subgroups in large samples of SZ and BD patients independently, and comparing their cognitive profiles. The utility of a cross-diagnostic clustering approach to understanding cognitive heterogeneity in these patients was also explored. METHOD: Hierarchical clustering analyses were conducted using cognitive data from 1541 participants (SZ n = 564, BD n = 402, healthy control n = 575). RESULTS: Three qualitatively and quantitatively similar clusters emerged within each clinical group: a severely impaired cluster, a mild-moderately impaired cluster and a relatively intact cognitive cluster. A cross-diagnostic clustering solution also resulted in three subgroups and was superior in reducing cognitive heterogeneity compared with disorder clustering independently. CONCLUSIONS: Quantitative SZ-BD cognitive differences commonly seen using group averages did not hold when cognitive heterogeneity was factored into our sample. Members of each corresponding subgroup, irrespective of diagnosis, might be manifesting the outcome of differences in shared cognitive risk factors.